eventyay git-commit.instructions.md

A set of Git rules for the fossasia/eventyay project, covering commits, branches, pull requests, tests, and CI. Git records code changes, while a pull request proposes them for review.

In plain words
What is it for?
Use it when writing commit messages, creating feature branches, opening pull requests against the dev branch, updating tests, and checking CI requirements.
Why use it?
It keeps changes focused, reviewable, and compatible with the repository’s development and merging process.

Instructions file for GitHub Copilot

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/fossasia/eventyay/git-commit
Clone the repo
git clone --depth 1 https://github.com/fossasia/eventyay

Made for: GitHub Copilot.

Per session 255 This file is loaded in full into every session.
When invoked 255 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00255 $0.00255
Opus 5 $0.00128 $0.00128
Sonnet 5 $0.00051 $0.00051
Haiku 4.5 $0.00026 $0.00026

Measured yesterday against content hash 56232ce44235, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

eventyay git-commit.instructions.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.github/instructions/git-commit.instructions.md · 26 lines

What it actually says

Git tool guideline

Commit

  • Write meaningful commit messages and maintain clean Git history.
  • The commit message should be concise, short enough to be displayed in one line for most Git clients. No need to say "Refactor xxx to improve readability and performance". Of course we know that we are refactoring code, and the reason is usually to improve readability and performance. Just say what you did.
  • When there are many things to say, the commit message should be split into two parts, separated by a blank line:
    • A short summary line following the brevity rule above.
    • A detailed description, which can be arbitrarily long.

Branching

  • Work in feature branches; open PRs against the dev branch.
  • Keep commits focused and atomic.

PR Expectations

  • All CI checks must pass before merging.
  • Keep diffs small and focused on a single concern.
  • Update or add tests for any changed behavior.
  • Only work inside this repository.
  • All changes must be self-contained; do not depend on code in external forks or unmerged upstream branches. You may reference issues for context, but the PR itself must be reviewable and workable on its own in this repo.
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 26 lines · 255 tokens per session scan A 56232ce44235

Subscribe to this mod's changes

eventyay git-commit.instructions.md is an instructions file published in the GitHub repository fossasia/eventyay (1,653 stars, last pushed yesterday), licensed Apache-2.0. It adds 255 tokens to every session, about $0.0013 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other instructions, from other repositories

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

buildNext

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

next.js AGENTS.md

Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

spec-kit AGENTS.md

Instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,040 tokens

langchain AGENTS.md

Instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,345 tokens